code: def core_retro_dataset_config_from_args(args, retro_args):
      return MultiSplitGPTDatasetConfig(
          is_built_on_rank=is_dataset_built_on_rank,
          random_seed=retro_args.retro_gpt_seed,
          sequence_length=retro_args.retro_gpt_seq_length,
          blend=args.data_path
          if args.data_path is not None
          else retro_args.retro_gpt_data_path,
          split=args.split,
          path_to_cache=args.data_cache_path,
          return_document_ids=retro_args.retro_return_doc_ids,
          split_preprocessing=retro_args.retro_gpt_split,
      )
  
file_path: megatron-lm/tools/retro/query/chunk_dataset.py
imports: import os
  import torch
  from megatron import get_args, get_retro_args, print_rank_0
  from megatron.core.datasets.blended_megatron_dataset_builder import BlendedMegatronDatasetBuilder
  from megatron.training import build_train_valid_test_datasets, update_train_iters
  from pretrain_gpt import is_dataset_built_on_rank
  from tools.retro.db.utils import get_indexed_dataset_infos
  from tools.retro.utils import get_num_chunks_per_sample
  from .multi_split_gpt_dataset import MultiSplitGPTDataset, MultiSplitGPTDatasetConfig
  from .utils import get_neighbor_dirname, get_query_workdir
label_desc: Use image node_id 1 for calling a global function with example usage: core_retro_dataset_config_from_args(args, retro_args) and returns: MultiSplitGPTDatasetConfig